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在 Google Cloud 控制台中运用您的技能

Nicolas Alvarez

成为会员时间:2025

黄金联赛

13130 积分
使用 Dataplex 构建数据网格 Earned Apr 19, 2025 EDT
Build Streaming Data Pipelines on Google Cloud Earned Feb 24, 2025 EST
Build Batch Data Pipelines on Google Cloud Earned Feb 15, 2025 EST
Build Data Lakes and Data Warehouses on Google Cloud Earned Feb 5, 2025 EST
Google Cloud 数据工程简介 Earned Jan 31, 2025 EST
Preparing for your Professional Data Engineer Journey Earned Jan 31, 2025 EST

完成入门技能徽章课程使用 Dataplex 构建数据网格,展示以下方面的技能:使用 Dataplex 构建数据网格, 以在 Google Cloud 上实现数据安全、治理和发现。您将在 Dataplex 中练习和测试自己在标记资产、分配 IAM 角色和评估数据质量方面的技能。

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In this course you will get hands-on in order to work through real-world challenges faced when building streaming data pipelines. The primary focus is on managing continuous, unbounded data with Google Cloud products.

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In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting. Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.

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在本课程中,您将了解 Google Cloud 数据工程、数据工程师的角色和职责,以及相关的 Google Cloud 产品和服务。您还将了解如何应对数据工程挑战。

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This course helps learners create a study plan for the PDE (Professional Data Engineer) certification exam. Learners explore the breadth and scope of the domains covered in the exam. Learners assess their exam readiness and create their individual study plan.

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